In today’s web-centric world, comparing the structure and design of web pages can play a vital role in various applications, from SEO to content management. This blog will guide you through the concept of HTML Similarity, focusing on its installation, functionality, and practical usage.

What is HTML Similarity?

The HTML Similarity package provides a set of functions aimed at measuring the similarity between web pages. It allows users to evaluate how closely two HTML documents resemble each other, based on both structural and stylistic attributes.

Installation

To get started with the HTML Similarity library, follow this simple installation step:

pip install html-similarity

How Does It Work?

HTML Similarity measures the resemblance between HTML documents using two main components: Structural Similarity and Style Similarity.

Structural Similarity

Think of Structural Similarity like comparing the skeletons of two buildings. Just as you would look at the arrangement and connection of beams and walls, the library uses sequence comparison of HTML tags to assess how similarly they are structured. Unlike tree edit distance—which is a more complex method—this approach is faster and more efficient.

Style Similarity

Style Similarity evaluates the aesthetic aspects of the HTML documents. Imagine decorating two rooms. While the layout is essential (structural similarity), the colors, patterns, and styles (like CSS classes) you choose significantly define their looks. This component calculates the Jaccard similarity of the CSS classes present in the documents.

Joint Similarity

Combining both structural and style similarities gives us the joint similarity metric:

joint_similarity = k * structural_similarity(document_1, document_2) + (1 - k) * style_similarity(document_1, document_2)

Here, the variable k allows you to balance the weight given to each similarity metric. Recommendations suggest using k=0.3 for optimal results, as it leans more on style similarity, which can provide richer insights into the relationship between documents.

Examples

Let’s look at a practical example to see how this works:

html_1 = "
First Document
Documents
Extra
"
html_2 = "
Second Document
Extra Documents
"

from html_similarity import style_similarity, structural_similarity, similarity

style_similarity(html_1, html_2)  # Result: 1.0
structural_similarity(html_1, html_2)  # Result: 0.909
similarity(html_1, html_2)  # Result: 0.955

In this example, the style similarity returns 1.0, indicating a perfect match in CSS classes, while the structural similarity is very high at 0.909, showing that the overall layout is quite similar too.

Troubleshooting

If you encounter any issues while working with HTML Similarity, here are some troubleshooting ideas:

• Ensure you have installed the correct package using pip install html-similarity.
• Double-check your HTML syntax; invalid markup can affect similarity calculations.
• Adjust the k value in the joint similarity formula if the results don’t meet your expectations.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

References

• The idea of sequence comparison is inspired by Page Compare.
• Additional concepts were derived from T. Gowda and C. A. Mattmann’s work, “Clustering Web Pages Based on Structure and Style Similarity,” presented at the 2016 IEEE Conference.
• Check out this slide presentation for a deeper understanding.

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.